Pyrad QPE Exercise

• An overview of pyrad is provided here.
• Pyrad documentation can be found here.
• Code is available at the github repository.

QPE Exercise¶

We are going to practice with the Pyrad config files to create a QPE processing data chain. The following data will be used:

• Rain gauge data from ARPA Lombardia.
• X-band radar data provided by ARPA Lombardia.
• Radar data from the MeteoSwiss radar at Monte Lema.
• Rain gauge data from MeteoSwiss

We have prepared for you a stub of the 3 config files to process the X-band radar data. Have a look at them here:

• main config file
• loc config file
• prod config file

If you execute pyrad using this config file you will get a projection on a map of the reflectivity of the 2nd elevation. Let’s try that:

1. Open the terminal
2. Go to erad2024/pyrad/config
3. execute: main_process_data.py qpe.txt --starttime 20240522160000 --endtime 20240522160000 --cfgpath ./
4. The created image is stored in the directory erad2024/pyrad/pyrad_outputs/QPE_ARPA2/2024-05-22/dBZ/EL1.3/

Exercise 1: Exploring the raw data¶

Can you generate similar maps for ZDR, RhoHV, KDP and PhiDP?

Have a look at other elevations as well.

Could you generate a pseudo-RHI for an azimuth of interest? (hint: a pseudo-ppi map is generated using the PSEUDORHI_IMAGE product)

Exercise 2: Clutter filtering¶

Generate an echoID dataset using the sanity check SAN process and filter all the data using the ECHO_FILTER dataset generator.

Exercise 3: Attenuation correction¶

Correct the reflectivity and the differential reflectivity using the ATTENUATION process.

Exercise 4: Hydrometeor classification¶

Use the semi-supervised hydrometeor classification in the HYDROCLASS process to obtain an hydro dataset

Exercise 5: Rainfall rate estimation¶

Use the hydro method in the RAINRATE process to get the rainfall rate

Exercise 6: Comparing radar rainfall rate with rain gauge measurements¶

Extract data at a point using the POINT_MEASUREMENT process and generate rain gauge-radar comparisons using TIME_SERIES products. The following rain gauges are available:

• 45.8500,8.0000 COL (Coldrerio)
• 45.843, 8.932 SBO (Stabio)
• 45.843, 8.932 GEN (Monte Generoso)
• 45.8333, 8.8167 IYVAV (Masnago)
• 45.8167,9.0667 IYCOV (Como)
• 45.6833,9.1833 IYMAR (Mariano Comense)
• 45.6833,9.1833 IYVAP (Varallo)
• 45.6833,9.1833 IYVEM (Vertemate)

Exercise 7: Projection into regular grid¶

Project the rainfall rate estimation into a regular grid using the GRID process. Plot the rainfall rate at several elevations.

Bonus questions:¶

• Use other rainfall rate estimators available on Pyrad
• Use alternative KDP processing methods
• Create config files to process Monte Lema radar data

Beyond QPE¶

Pyrad has much more features available than just QPE. Have a look at the two config file sets that covers other projects discussed in this course:

• Dual-Doppler analysis using PyDDA
• Quasi-Vertical profiles

There are many more examples of config files available in the Pyrad examples repository.

Thank You for your participation in the course!¶

If you have further questions, or you encounter bugs, or the documentation is not clear do not hesitate to open an issue.

Contributions are very welcomed!!!¶

Open an issue so that we can discuss your contribution and make sure together that if fits into the software